The semiconductor industry needs to become more sustainable in a world of increasing demand – optimization holds the key.
Over the past decade, industries worldwide have had to tackle the issue of sustainability as a matter of increasing urgency, with the need to mitigate greenhouse gas emissions becoming a major factor in companies’ operations and processes. For many, this has been a difficult accommodation to make, because it has forced them to change the way they work. On the other hand, addressing the climate crisis has acted as a catalyst for the transition to more innovative and efficient methods of production and manufacture.
The semiconductor industry is at the heart of our modern technological society, and as recent supply chain issues have demonstrated, any slowdown in production has a significant knock-on effect on multiple other sectors. Given its centrality, and the need to maintain output, sustainability hasn’t always been as high on the agenda of chip companies as it should have been. However, ignoring the serious environmental impact that semiconductor industry has on the world around it is no longer tenable.
According to McKinsey, “large semiconductor fabs use as much as 100 megawatt-hours of energy each hour, which is more than many automotive plants or oil refineries do.” They also point out that an average fab will use as much power in a year as 50,000 homes – that’s enough electricity to run a small town. And as the demand for semiconductors continues to grow, and the production process becomes ever more sophisticated, on its current trajectory, the industry’s energy usage is only set to increase.
Electricity production is of course a major source of CO2 emissions, with the majority of power stations still fuelled by hydrocarbons such as coal and gas. It’s an inescapable fact that using more energy means emitting more greenhouse gases – so reducing energy consumption is an obvious way for the semiconductor industry to improve its environmental footprint. But given the demand outlined above, how is this realistically possible?
If we look at where the energy in fabs is actually being used, a solution becomes clearer. McKinsey calculates that approximately 55% of energy consumption is generated by running tools. Given that many of the machines on a fab’s production line are in use 24/7, this perhaps isn’t that surprising. And as I noted earlier, chip companies aren’t about to reduce this level of operation just to become more environmentally-friendly – for both them and other industries, the stakes are too high to do anything that would threaten production.
This is reflected in the KPIs that fabs work to, which are primarily based on cycle time, throughput and yield – energy consumption has historically been very much a secondary consideration. However, production doesn’t completely exist in a bubble, and as with any company, the bottom line is the ultimate driver of operations. Cost reduction is just as important as revenue generation. McKinsey notes that, depending on local electricity tariffs, energy consumption can account for up to 30% of a fab’s operating costs. And with the price of energy continuing to rocket, that figure is almost certain to increase.
So given that energy is a factor that affects both production costs and sustainability, reducing consumption is edging its way up the fab’s table of priorities. Yet what if you could address both those primary KPIs and the need to be greener at the same time?
Optimization technology is the key. It’s a point I keep returning to, but if chip companies are to deal with the challenges that the future is sure to keep throwing at them, then they have to start adopting best-in-class smart manufacturing practices and software.
To properly optimize the way in which the fab works, we have to first understand exactly what the state of the entire WIP is in real time. By mapping the current state of the fab’s operations, it’s possible to identify where bottlenecks are occurring due to sub-optimal scheduling. And in our experience of working with different fabs, the tools where queues usually occur are involved in the most energy-intensive stages of the production process – for example, photolithography, diffusion furnace and in the cleanroom.
Using optimization software to reduce bottlenecks by improving how wafers move through energy-intensive tools, the fab’s primary KPIs can be met and energy consumption at these tools can be reduced. For example, doing more moves with fewer tools at the photo stage means that it’s possible for some tools to be left idle. Or doing the same moves but with fewer batches at the furnace stage means fewer energy-intensive furnace runs.
At the tail end of last year, I gave a presentation at the Smart & Green Manufacturing Summit, as part of Semicon Europa 2022, that outlined how our scheduling optimization software has already achieved these goals in the real world.
Optimization technology can also be used to directly control the energy consumption of less busy tools as well. As long as those areas that are prone to bottlenecks are running efficiently, and all primary KPIs are being met, tools in other areas can be optimized specifically for energy conservation – for instance, powered down because the scheduling technology has identified that they aren’t required or don’t have to be operated at their maximum rate.
Most of the larger semiconductor companies are looking at ways to be greener and meet net zero goals, although carbon offsetting is currently playing more of a role than making manufacturing processes more energy efficient. However, some companies are addressing the issue head-on and looking at ways to control their fabs’ energy use – for example, Flexciton, Imperial College London and the Technical University of Munich are currently working together on a project to map Infineon’s energy consumption, with the aim to better understand how smarter decisions can help the company reduce its carbon emissions.
The demand for semiconductors is only going to grow in the decades ahead, but a reckoning over the industry’s attitude to sustainability will be reached much sooner than that unless energy reduction becomes one of its key priorities. Yet by working smarter and re-evaluating their production processes, it’s absolutely possible for companies to improve throughput and yield while at the same time being more energy efficient.
Author: Jamie Potter, CEO and Cofounder
Staying ahead in smart manufacturing technologies has become paramount for global competitiveness. This topic was the focal point of the recent panel discussion webinar hosted by Flexciton.
The semiconductor industry's journey toward fully autonomous manufacturing is underway, driven by advanced technologies and strategic investment. Staying ahead in smart manufacturing technologies has become paramount for global competitiveness. This topic was the focal point of the recent panel discussion webinar, hosted by Jamie Potter, Flexction CEO & Cofounder. The panel featured industry leaders representing fabs and suppliers: Matthew Johnson, VP of Wafer Fab Operations at Seagate; Patrick Sorenson, Industrial Engineer at Microchip Technology; Francisco Lobo, CEO of Critical Manufacturing; and Madhav Kidambi, Technical Marketing Director at Applied Materials.
The panel discussion was initiated with a presentation of the findings from Flexciton's inaugural Front End Manufacturing Insights survey, conducted among fabs in the US, Europe, and Asia. Key takeaways included:
These insights laid a strong foundation for a lively discussion, highlighting the shared vision while addressing divergent strategies and challenges.
Francisco Lobo emphasized the importance of starting with what’s available when building scalable solutions.
“Instead of building a complete model from scratch, leverage existing standards and your MES infrastructure. Begin with a pragmatic approach and evolve as you learn.”
This iterative strategy ensures companies can start deriving value early, without waiting years for a perfect model to be developed.
While many fabs postpone investments during downcycles, Matthew Johnson emphasizes that smart manufacturing investments should be continuous rather than cyclical. He highlighted the strategic advantage of such approach:
“In down cycles, you often need these solutions the most. For example, using smart manufacturing to scale metrology tools through sampling can significantly stretch your existing resources without capital-heavy investments.”
His insight underscores how downturns provide a window to refine processes for long-term gains.
Securing leadership support for smart manufacturing investments remains challenging when benefits aren't immediately apparent. Patrick Sorenson shares that the ROI justification was easier during the recent upcycle:
"If we just get a few more lots out of the fab when we have more demand than capacity, that will pay for itself."
In other scenarios, focus on demonstrating benefits through yield improvements, capital avoidance, or labor efficiency.
Madhav Kidambi observed a growing consensus around the end goal of autonomous manufacturing, even as companies differ in their pathways:
“The vision of Lights Out manufacturing is clear, but strategies are evolving as companies learn how to justify and sequence investments to sustain the journey.”
A key theme emerging from the discussion is the importance of collaboration between suppliers and fabs. This includes:
As the industry progresses toward autonomous manufacturing, success will depend on:
As Matt from Seagate concludes,
"Fab operation is really a journey of continuous improvement, and the pursuit of smart technologies is a fundamental tenet of our strategy to ensure that we meet the objectives as an organization."
The conversation is packed with actionable insights on overcoming barriers, achieving quick wins, and navigating the complexities of smart manufacturing adoption. Don’t miss out—click here to watch the full discussion recording.
Innovate UK, part of UK Research and Innovation, has invested in Flexciton and Seagate Technology's production planning project to help improve UK semiconductor manufacturing.
London, UK – 1 Oct – Flexciton, a UK-based software company at the forefront of autonomous semiconductor manufacturing solutions, is excited to announce investment from Innovate UK in a strategic collaboration with Seagate Technology’s Northern Ireland facility. Innovate UK, the UK’s innovation agency, drives productivity and economic growth by supporting businesses to develop and realize the potential of new ideas. As part of their £11.5 million investment across 16 pioneering projects, this collaboration will help develop and demonstrate cutting-edge technology to boost semiconductor manufacturing efficiency and enhance the UK’s role in the global semiconductor supply chain.
Jamie Potter, CEO and Cofounder of Flexciton, commented:
"We are thrilled to partner with Seagate Technology to bring yet another Flexciton innovation to market. By combining our autonomous scheduling system with Flex Planner, we are enhancing productivity in semiconductor wafer facilities and driving greater adoption of autonomous manufacturing."
The partnership aligns directly with the UK government’s National Semiconductor Strategy, which seeks to secure the UK’s position as a key player in the global semiconductor industry. Flexciton’s contribution to this strategy is not just a testament to its cutting-edge technology but also highlights the company’s role in reinforcing supply chain resilience and scaling up manufacturing capabilities within the UK.
At the heart of this project is Flex Planner, the first closed-loop production planning solution for semiconductor manufacturing with the ability to control the flow of WIP in a fab over the next 2-4 weeks, autonomously avoiding dynamic bottlenecks, reducing cycle times, and improving on-time delivery performance.
The UK government’s investment in semiconductor innovation underlines its commitment to fostering cutting-edge solutions that bolster the sector’s growth. The semiconductor industry is projected to grow from £10 billion to £17 billion by 2030, with initiatives like this collaboration driving the innovation necessary to achieve these goals.
Flexciton’s partnership with Seagate exemplifies how collaboration between technology innovators and manufacturers can lead to transformative advances in the industry. The funding from Innovate UK enables both companies to develop and test solutions that not only enhance productivity but also position the UK as a critical link in the global semiconductor ecosystem.
Flexciton is pioneering autonomous technology for production scheduling and planning in semiconductor manufacturing. Leveraging advanced AI and optimization technology, we tackle the increasing complexity of chipmaking processes. By simplifying and streamlining wafer fabrication with our next-generation solutions, we enable semiconductor fabs to significantly enhance efficiency, boost productivity, and reduce costs. Empowering manufacturers with unmatched precision and agility, Flexciton is revolutionizing wafer fabrication to meet the demands of modern semiconductor production.
For media inquiries, please contact: media@flexciton.com
The semiconductor industry is set to receive $1tn in investment over the next six years, driven by AI and advanced technologies, with over 100 new wafer fabs expected. However, labor shortages continue to pose a challenge, pushing the need for autonomous wafer fabs to ensure continued growth.
Over the next 6 years, the semiconductor industry is set to receive around $1tn in investment. The opportunities for growth – driven by the rapid rise of AI, autonomous and electric vehicles, and high-performance computing – are enormous. To support this anticipated growth, over 100 new wafer fabs are expected to emerge worldwide in the coming years (Ajit Manocha, SEMI 2024).
However, a significant challenge looms: labor. In the US, one-third of semiconductor workers are now aged 55 or older. Younger generations are increasingly drawn to giants like Google, Apple and Meta for their exciting technological innovation and brand prestige, making it difficult for semiconductor employers to compete. In recent years, the likelihood of employees leaving their jobs in the semiconductor sector has risen by 13% (McKinsey, 2024).
To operate these new fabs effectively, the industry must find a solution. The Autonomous Wafer Fab, a self-optimizing facility with minimal human intervention and seamless production, is looking increasingly likely to be the solution chipmakers need. This vision, long held by the industry, now needs to be accelerated due to current labor pressures.
Thankfully, rapid advancements in artificial intelligence (AI) and Internet of Things (IoT) mean that the Autonomous Wafer Fab is no longer a distant dream but an attainable goal. In this blog, we will explore what an Autonomous Wafer Fab will look like, how we can achieve this milestone, the expected outcomes, and the timeline for reaching this transformative state.
Imagine a wafer fab where the entire production process is seamlessly interconnected and self-regulating, free to make decisions on its own. In this autonomous environment, advanced algorithms, IoT, AI and optimization technologies work in harmony to optimize every aspect of the manufacturing process. From daily manufacturing decisions to product quality control and fault prediction, every step is meticulously coordinated without the need for human intervention.
Intelligent Scheduling and Planning: The heart of the autonomous fab lies in its scheduling and planning capabilities. By leveraging advancements such as Autonomous Scheduling Technology (AST), the fab has the power to exhaustively evaluate billions of potential scenarios and guarantee the optimal course for production. This ensures that all constraints and variables are considered, leading to superior outcomes in terms of throughput, cycle time, and on-time delivery.
Real-Time Adaptability: An autonomous fab is equipped with sensors and IoT devices that continuously monitor the production environment. These devices can feed real-time data into the scheduling system, allowing it to dynamically adjust schedules and production plans in response to any changes or disruptions.
Digital Twin: Digital Twin technology mirrors real-time operations through storing masses of data from sensors and IoT devices. This standardized data schema allows for rapid introduction of new technologies and better scalability. Moreover, by simulating production processes, it helps to model possible scenarios – such as KPI adjustments – within the specific constraints of the fab.
Predictive maintenance: Predictive maintenance systems will anticipate equipment failures before they occur, reducing downtime and extending the lifespan of critical machinery. This proactive approach ensures that the fab operates at peak efficiency with minimal interruptions. Robotics will carry out the physical maintenance tasks identified by these systems, and when human intervention is necessary, remote maintenance capabilities will allow technicians to diagnose and address issues without being on-site.
The Control Room: In an autonomous fab, decision-making is driven by data and algorithms. The interconnected system can balance trade-offs between competing objectives, such as maximizing throughput while minimizing cycle time, with unparalleled precision. That said, critical decisions such as overall fab objectives may still be left to humans in the “control room”, who could be on the fab site or 9000 km away…
Achieving the vision of an Autonomous Wafer Fab requires a multi-faceted approach that integrates technological innovation, strategic investments, and a cultural shift towards embracing automation. Here are the key steps to pave the way:
A Robust Roadmap: All fabs within an organization need to have a common vision. Key milestones need to be laid out to help navigate each fab through the transition with clear actions at each stage. SEMI’s smart manufacturing roadmap offers an insight into what this could look like.
Investing in Novel Technologies: The pivotal step towards autonomy is investing in the latest technologies, including AI, machine learning, AST, and IoT. These technologies form the backbone of the autonomous fab, enabling intelligent planning and scheduling, real-time monitoring, and adaptive control.
Data Integration and Analytics: A crucial aspect of autonomy is the seamless integration of data from various sources within the fab. By harnessing big data analytics, fabs can not only gain deep insights into their operations, but they will have the correct data in place to support autonomous systems further down the line.
Developing Skilled Workforce: While the goal is to minimize human intervention, the semiconductor industry will still require skilled professionals who can manage and maintain advanced systems. Investing in workforce training and development to fill the current void is essential to ensure a smooth transition.
Collaborative Ecosystem: Even the biggest of chipmakers is unlikely to reach the autonomous fab all on their own. Collaboration with technology providers, research institutions, and industry partners will be key. Sharing knowledge and best practices can accelerate the development and deployment of autonomous solutions.
Pilot Programs and Gradual Implementation: Transitioning to an autonomous fab should be approached incrementally. Starting with pilot programs to test and refine technologies in a controlled environment will help identify challenges and demonstrate the benefits. Gradual implementation allows for continuous improvement and adaptation.
The transition to an Autonomous Wafer Fab promises a multitude of benefits that will revolutionize semiconductor manufacturing:
Enhanced Efficiency: By optimizing production schedules and processes, autonomous fabs will achieve higher throughput and better resource utilization. This translates to increased production capacity and reduced operational costs.
Better Quality: Advanced process control and real-time adaptability ensure consistent product quality, minimizing defects and rework. This leads to higher yields and greater customer satisfaction.
Reduced Downtime: Predictive maintenance and automated decision-making reduce equipment failures and production interruptions. This results in higher uptime and more reliable operations.
Improved Flexibility: Autonomous fabs can quickly adapt to changing market demands and production requirements. This flexibility enables manufacturers to respond rapidly to customer needs and stay competitive in a dynamic industry.
Cost Savings: The efficiencies gained from autonomous operations lead to significant cost savings. Reduced labor intensity, lower material waste, and optimized energy consumption contribute to a more cost-effective production process.
The journey towards an Autonomous Wafer Fab is well underway, but the timeline for full realization varies depending on several factors, including technological advancements, industry adoption, and investment levels. However, significant progress is expected within the next decade.
Short-Term (1-3 Years):
Medium-Term (3-7 Years):
Long-Term (7-10 Years and Beyond):
The pathway to the Autonomous Wafer Fab is a transformative journey that holds immense potential for the semiconductor industry. By embracing advanced technologies, fostering collaboration, and investing in the future workforce, fabs can unlock unprecedented levels of efficiency, quality, and flexibility. Autonomous Scheduling Technology, as a key pillar, will play a crucial role in this evolution, driving the industry towards a future where production is seamless, self-optimizing, and truly autonomous. The vision of an Autonomous Wafer Fab is not just a distant possibility but an imminent reality, poised to redefine the landscape of semiconductor manufacturing.
Now available to download: our new Autonomous Scheduling Technology White Paper
We have just released a new White Paper on Autonomous Scheduling Technology (AST) with insights into the latest advancements and benefits.
Click here to read it.